Hybrid Feedback Control Methods for Robust and Global Power Conversion

In this paper, the applicability and importance of hybrid system tools for the design of control algorithms for energy conversion in power systems is illustrated in two hybrid control designs, one pertaining to DC/DC conversion and the other to DC/AC inversion. In particular, the mathematical models considered consist of constrained switched differential equations/inclusions that include all possible modes of operation of the systems. Furthermore, the obtained models can be analyzed and their algorithms designed using hybrid system tools so as to attain key desired properties, such as stability, forward invariance, global convergence, and robustness. We argue that hybrid system tools provide a systematic approach for analysis and controller design of power systems. In particular, hybrid system tools usually leads to power quantities that have better performance and robustness to state perturbations. Furthermore, they provide guidelines on how to tune the controller parameters based on design requirements. These factors motivate the implementation of the proposed hybrid controllers in modern power conversion systems that use renewable energy sources. Simulations illustrating the main results and benchmark tests are included

Mechanics of bio–hybrid systems

Bio–hybrid system are morphing structures whose shaping can be electrically driven and strongly depends on the geometrical and mechanical characteristics of the system. The estimation of those characteristics which allow for getting target shapes is a great challenge. We present and discuss an approximate model for narrow bio–hybrid strips which works well in plane bending. A generalization towards three–layers bio–hybrid system is presented

Time-Staging Enhancement of Hybrid System Falsification

Optimization-based falsification employs stochastic optimization algorithms to search for error input of hybrid systems. In this paper we introduce a simple idea to enhance falsification, namely time staging, that allows the time-causal structure of time-dependent signals to be exploited by the optimizers. Time staging consists of running a falsification solver multiple times, from one interval to another, incrementally constructing an input signal candidate. Our experiments show that time staging can dramatically increase performance in some realistic examples. We also present theoretical results that suggest the kinds of models and specifications for which time staging is likely to be effective

A bidirectional fluorescent two-hybrid system for monitoring protein–protein interactions

Two-hybrid systems have been the cornerstone of research into protein–protein interactions, but these systems typically rely on life/death reporters that put additional selective pressure on the host organism, and potentially lead to false positives. Here we report a bidirectional fluorescence-based bacterial two- hybrid system that enables both the association and dissociation of a given protein–protein interaction to be monitored. The functionality of this system and its compatibility with FACS screening are demon- strated in the forward and reverse direction using known interacting protein-partners and their cyclic peptide inhibitors. The reported fluorescent two-hybrid system may be used in the forward direction for the identification of interacting protein partners, or as a reverse two-hybrid system for the high- throughput identification of protein–protein interaction inhibitors

Safe Neighborhood Computation for Hybrid System Verification

For the design and implementation of engineering systems, performing model-based analysis can disclose potential safety issues at an early stage. The analysis of hybrid system models is in general difficult due to the intrinsic complexity of hybrid dynamics. In this paper, a simulation-based approach to formal verification of hybrid systems is presented.Comment: In Proceedings HAS 2014, arXiv:1501.0540

Novel hybrid extraction systems for fetal heart rate variability monitoring based on non-invasive fetal electrocardiogram

This study focuses on the design, implementation and subsequent verification of a new type of hybrid extraction system for noninvasive fetal electrocardiogram (NI-fECG) processing. The system designed combines the advantages of individual adaptive and non-adaptive algorithms. The pilot study reviews two innovative hybrid systems called ICA-ANFIS-WT and ICA-RLS-WT. This is a combination of independent component analysis (ICA), adaptive neuro-fuzzy inference system (ANFIS) algorithm or recursive least squares (RLS) algorithm and wavelet transform (WT) algorithm. The study was conducted on clinical practice data (extended ADFECGDB database and Physionet Challenge 2013 database) from the perspective of non-invasive fetal heart rate variability monitoring based on the determination of the overall probability of correct detection (ACC), sensitivity (SE), positive predictive value (PPV) and harmonic mean between SE and PPV (F1). System functionality was verified against a relevant reference obtained by an invasive way using a scalp electrode (ADFECGDB database), or relevant reference obtained by annotations (Physionet Challenge 2013 database). The study showed that ICA-RLS-WT hybrid system achieve better results than ICA-ANFIS-WT. During experiment on ADFECGDB database, the ICA-RLS-WT hybrid system reached ACC > 80 % on 9 recordings out of 12 and the ICA-ANFIS-WT hybrid system reached ACC > 80 % only on 6 recordings out of 12. During experiment on Physionet Challenge 2013 database the ICA-RLS-WT hybrid system reached ACC > 80 % on 13 recordings out of 25 and the ICA-ANFIS-WT hybrid system reached ACC > 80 % only on 7 recordings out of 25. Both hybrid systems achieve provably better results than the individual algorithms tested in previous studies.Web of Science713178413175